preditc.py

import plotly.express as px
import pandas as pd
import json


def predict_expected_position(lat, lon, alt, ground_speed, heading, climb):
    # TODO:
    pass

# example data structure
# data = {
#     "lat":[50.0,51.0,...],
#     "lon":[13.0,14.0,...],
#     "color":["00ff00","00ff00",...]
# }
def parse_json_to_dataframe(filepath):
    f = open(filepath,"r")
    raw = json.load(f)
    f.close()
    data = {
        "lat":[],
        "lon":[],
        "color": []
    }

    for entry in raw["trace"]:
        # documentation at https://www.adsbexchange.com/version-2-api-wip/
        lat,lon,alt,ground_speed,heading,climb = entry[1:7]

        predicted_point = predict_expected_position(lat, lon, alt, ground_speed, heading, climb)

        # TODO: calculate uncertainty
        data["lat"].append(lat)
        data["lon"].append(lon),
        data["color"].append("FF00FF"),


    return pd.DataFrame(data=data)

# source: https://samples.adsbexchange.com/traces/2023/10/01/ff/trace_full_a94bff.json
data = parse_json_to_dataframe("../data/trace_full_a94bff.json")

fig = px.line_mapbox(data, lat="lat", lon="lon", color="color", zoom=3, height=1000)

fig.update_layout(mapbox_style="open-street-map", mapbox_zoom=4, mapbox_center_lat = 41,
    margin={"r":0,"t":0,"l":0,"b":0})

fig.show()